Job Description

Overview:

We're evolving our experimentation platform that empowers product teams to make bold, data-driven decisions at scale.



As a

Senior Data Scientist (Experimentation)

, you will be a technical and strategic lead in how we design, analyze, and learn from experiments across the organization.


You will own complex experimentation problems end-to-end: shaping hypotheses, defining success metrics, selecting and inventing methodologies, and translating results into clear strategic recommendations. Beyond individual analyses, you will influence standards, mentor others, and help mature our experimentation culture, tooling, and practices.


This role is ideal for someone who thrives at the intersection of advanced statistics, product strategy, and storytelling and who enjoys setting direction, not just executing.


Responsibilities:
Collaborate with cross functional teams to turn ambiguous business questions into testable hypotheses. Design high quality experiments that balance statistical rigor and velocity, using modern causal inference and experimentation techniques. Perform and lead deep dive analyses in SQL and Python to uncover insights and measure impact, with a strong focus on query optimization, performance, and scalable analytics. Apply advanced statistical approaches, including Bayesian inference, to estimate treatment effects, support decision-making under uncertainty, and incorporate prior knowledge. Design, implement, and maintain advanced experimentation and optimization methodologies, such as adaptive testing approaches, variance reduction, robust metric frameworks, and causal inference techniques. Develop and apply AI-powered analytics and decision-support tools to enhance experimentation workflows, insight generation, leveraging Snowflake's ML and Cortex capabilities. Ensure the integrity and reliability of experimentation through data quality checks, monitoring frameworks, and automated validation. Develop data pipelines and transformations using SQLMesh, with Airflow orchestration for scheduled monitoring and alerting. Build dashboards, visualizations, and decision-making tools using Streamlit, Power BI, or similar platforms. Communicate findings clearly to stakeholders at all levels from technical deep dives to executive summaries. Develop a strong understanding of the business to proactively identify opportunities for experimentation and optimization. Contribute to our data culture through mentorship, knowledge-sharing, and team collaboration

Qualifications:
A quantitative degree in Mathematics, Statistics, Data Science, Computer Science, Physics, Economics, Engineering, or similar

Experience :

5+ years of experience in data science, experimentation, analytics, or a related quantitative role. Advanced SQL skills and strong proficiency in Python for analysis and experimentation workflows. Deep understanding of frequentist and Bayesian statistics, causal inference, and experimental design in real-world settings. Experience with probabilistic programming (PyMC, Stan, NumPyro, or similar) or advanced machine learning frameworks. Experience building dashboards and analytical tools using modern visualization platforms (Streamlit, Power BI, Tableau, or similar platforms.) Familiarity with variance reduction techniques or regression modelling. * Proven ability to influence decisions and work effectively with cross-functional, distributed teams.